Bioinformatics analysis and validation of novel biomarkers and competitive endogenous RNA networks involved in pyroptosis in diabetic nephropathy.

Diabetic nephropathy (DN) is one of the major complications of diabetes mellitus. Pyroptosis is a type of programmed cell death that is closely related to the development of DN, however the molecular mechanism of pyroptosis in the development of DN is still unclear. The aim of this study is to identify pyroptosis-related potential biomarkers and competing endogenous RNA (ceRNA) networks in DN. The differentially expressed pyroptosis-related genes (DEPRGs) were identified using R software from Gene Expression Omnibus (GEO) database. In total, 4 significantly upregulated hub DEPRGs (CASP1, TXNIP, IRF9, and TRAF3) were selected and verified by machine learning techniques. Receiver Operating Curve (ROC) to assess the diagnostic value of pivotal DEPRGs. Immune infiltration was analysed using the CIBERSORT algorithm in R software. Then, differentially expressed miRNAs (DEmiRNAs) and lncRNAs (DElncRNAs) were obtained from the GEO database, respectively. The hub DEPRGs-associated ceRNA network was constructed. Finally, DN rats were induced by high-sugar and high-fat diet combined with an intraperitoneal injection of STZ. The expression of pyroptosis-related proteins and 4 hub DEPRGs were detected in rats' kidney tissues using Western blotting. The DN pyroptosis-related ceRNA networks constructed by hub genes were validated both in clinical samples and DN rat model using real-time PCR (qRT-PCR). Our results indicated that the ceRNA network consisting of key genes might be a potential regulatory axis for pyroptosis in DN.